An enhanced Doppler resolution and sidelobe suppression have long been practical issues for moving target detection using Golay complementary waveforms. In this paper, Golay complementary waveform radar returns are combined with a proposed processor, the pointwise thresholding processor (PTP). Compared to the pointwise minimization processor (PMP) illustrated in a previous work, which could only achieve a Doppler resolution comparable to existing methods, this approach essentially increases the Doppler resolution to a very high level in theory. This study also introduced a further filtering process for the delay-Doppler map of the PTP, and simulations verified that the method results in a delay-Doppler map virtually free of range sidelobes.

Ground moving targets with complex motions often appear seriously dislocated and smeared in synthetic aperture radar (SAR) imagery due to non-cooperative motion. Refocusing such targets in SAR is challenging because of unknown motion parameters. In this paper, a novel SAR moving target imaging method based on adaptive phase tracking (MTIm-APT) is proposed. First, the Hough transform (HT) and the second(2nd)-order Keystone transform (SOKT) are performed to correct the range migration. Second, the Doppler phase can be adaptively tracked based on the improved extended Kalman filter (EKF). With the tracked Doppler phase, the motion parameters required for moving target imaging is estimated. Finally, the moving target is well-focused after motion parameters compensation since the high-order Doppler phase errors are efficiently eliminated. Unlike existing research that only considers the 2nd- or third(3rd)-order Doppler phase, the proposed method considers higher-order Doppler parameters which can be simultaneously estimated, thus eliminating error propagation effect. More importantly, due to the suboptimal filtering characteristics of EKF, the proposed method maintains excellent imaging performance at lower signal-to-noise ratio (SNR) than classical PGA. On the other hand, our method has a certain advantage in computational efficiency. Both simulated and real data processing results are provided to validate the feasibility and effectiveness of the proposed SAR MTIm-APT method.

To solve the problem of the moving target synthetic aperture radar (SAR) imaging from an incomplete echo, we proposed a novel SAR imaging method for the moving target with the azimuth missing data (MTIm-AMD) in this article. Instead of directly reconstructing the moving target image using the sparse SAR imaging method, we estimate and reconstruct the noncooperative moving target's complete echo from the azimuth incomplete echo based on its sparsity. At first, the noncooperative moving target's motion parameters are estimated from the incomplete echo. Then, to ensure that the complete echo can be well reconstructed using the compressed sensing method, these parameters are exploited to design a phase compensation function. Finally, using the reconstructed data, the fine-focused moving target can be obtained via the traditional SAR imaging algorithm. The simulation and experiment data results verify the effectiveness of the proposed MTIm-AMD method and demonstrate that the moving target can be fine imaging when the echo signal-to-noise ratio (SNR) is higher than $-$ 20 dB and the azimuth missing ratio (AMR) is less than 70%. This implies that the proposed MTIm-AMD method achieves satisfactory robustness to echo SNR and can handle most AMR cases.

This paper proposes an Along-Track Swarm Synthetic Aperture Radar (ATS-SAR) system to accomplish the high frame rate and enhance imaging resolution simultaneously. Unlike the current along-track Multistatic SAR (Multi-SAR), each platform of the proposed ATS-SAR only collects part of the aperture data. Then, the bistatic pair acquisitions of ATS-SAR are transformed into virtual monostatic sub-apertures, and a large aperture is combined in a short time. Considering the practical motion state difference of each individual platform, various ATS-SAR echo models are thoroughly investigated and established. Furthermore, a Sub-Aperture Collaboration Imaging algorithm for ATS-SAR (SACIm-ATS) based on sparse constraints is also proposed. An effective phase compensation function is designed to improve echo sparsity by homogenizing the ATS-SAR echo. Then, the compressed sensing method can be utilized to accurately estimate more azimuth data, obtaining a higher azimuth resolution. Simulations and a real measured experiment are carried out to verify the effectiveness of the proposed ATS-SAR and the SACIm-ATS algorithm. Compared with the state-of-the-art imaging algorithms, the proposed SACIm-ATS algorithm can significantly enhance the ATS-SAR imaging performance.

Refocusing moving targets in synthetic aperture radar (SAR) poses inherent challenges. The difficulty is amplified when SAR raw data are missing in the azimuth direction, mainly because of the unknown motion parameters of non-cooperative targets. Estimating these parameters from SAR azimuth missing data (SAR-AMD) is notably more challenging than from complete echoes. To address this problem, we propose the MPE-CM method, a fast and robust motion parameter estimation method for SAR-AMD based on contrast maximization. Initially, following the range walk correction (RWC) by Keystone transform (KT), a coarse-focused image is derived in the range-Doppler (RD) domain by constructing a phase compensation function with varying focusing factors. Subsequently, the estimation of motion parameters is converted into the estimation of focusing factors, which is accomplished through the maximization of contrast in the coarse-focused image. Concurrently, we propose a Five-Point method to efficiently and robustly determine the focusing factor. Finally, the along-range and azimuth velocities can be retrieved from the estimated focusing factor and Doppler shift, where the Doppler shift is obtained by identifying the peak energy shift of the coarse-focused image. The proposed MPE-CM method, ensures computational efficiency through a fast and robust approach, while coherent processing improves its anti-noise performance. The experimental results demonstrate the effectiveness of the proposed MPE-CM method in SAR-AMD.

As a novel configuration of along-track Multistatic SAR (Multi-SAR), the high frame rate Along-Track Swarm SAR (ATS-SAR) has garnered significant attention in recent years due to its exceptional efficiency in reducing data acquisition time. Motivated by its potential for high-resolution imaging of moving targets, this paper investigates the application of ATS-SAR in moving target imaging. However, high frame rate ATS-SAR-based moving target imaging confronts two critical challenges: time-space coupling and partial data loss in moving target echoes. To address these challenges, we first conduct a comprehensive analysis and theoretical derivation of the moving target echo model under the high frame rate ATS-SAR configuration. Subsequently, we propose an innovative motion parameter estimation algorithm that exploits unique echo characteristics to achieve high-performance imaging. Furthermore, we introduce the highresolution, high frame rate ATS-SAR Sub-Aperture Collaborative Imaging algorithm for Moving Targets (MT-SACIm-ATS). Extensive simulations and a real measured experiment validate the effectiveness of the MT-SACIm-ATS algorithm, demonstrating imaging performance that closely approximates reference imaging results. Comparative analysis with several state-of-the-art algorithms further highlights the superiority of the proposed approach in terms of resolution and robustness.